Übersicht			Auf mobile öffnen

Lieferstatus:	Auf Bestellung (Lieferzeit unbekannt)
Veröffentlichung:	November 2018
Genre:	Naturwissensch., Medizin, Technik
	Artificial Intelligence / Automated Pattern Recognition / B / Big Data / Big Data/Analytics / Business mathematics & systems / Communications Engineering, Networks / Computational Intelligence / Data Mining / Data Mining and Knowledge Discovery / Electrical Engineering / engineering / Expert systems / knowledge-based systems / IT in Business / pattern recognition mehr...
ISBN:	9783319978635
EAN-Code:	9783319978635
Verlag:	Springer EN
Einband:	Gebunden
Sprache:	English
Serie:	Unsupervised and Semi-Supervised Learning
Dimensionen:	H 235 mm / B 155 mm / D 17 mm
Gewicht:	471 gr
Seiten:	187
Illustration:	IX, 187 p. 63 illus., 31 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen
Zus. Info:	EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025.
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

This book highlights the state of the art and recent advances in Big Data clustering methods and their innovative applications in contemporary AI-driven systems. The book chapters discuss Deep Learning for Clustering, Blockchain data clustering, Cybersecurity applications such as insider threat detection, scalable distributed clustering methods for massive volumes of data; clustering Big Data Streams such as streams generated by the confluence of Internet of Things, digital and mobile health, human-robot interaction, and social networks; Spark-based Big Data clustering using Particle Swarm Optimization; and Tensor-based clustering for Web graphs, sensor streams, and social networks. The chapters in the book include a balanced coverage of big data clustering theory, methods, tools, frameworks, applications, representation, visualization, and clustering validation.